Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations1043
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory106.1 KiB
Average record size in memory104.1 B

Variable types

Numeric12
Categorical1

Alerts

Al is highly overall correlated with B and 6 other fieldsHigh correlation
B is highly overall correlated with Al and 10 other fieldsHigh correlation
C is highly overall correlated with Al and 3 other fieldsHigh correlation
Co is highly overall correlated with B and 4 other fieldsHigh correlation
Cr is highly overall correlated with Al and 7 other fieldsHigh correlation
Mo is highly overall correlated with Al and 6 other fieldsHigh correlation
Nb is highly overall correlated with B and 1 other fieldsHigh correlation
Ni is highly overall correlated with BHigh correlation
Ta is highly overall correlated with Al and 6 other fieldsHigh correlation
Target is highly overall correlated with Al and 4 other fieldsHigh correlation
Ti is highly overall correlated with B and 5 other fieldsHigh correlation
W is highly overall correlated with Al and 4 other fieldsHigh correlation
Zr is highly overall correlated with B and 1 other fieldsHigh correlation
Ti has 121 (11.6%) zeros Zeros
Ta has 436 (41.8%) zeros Zeros
Nb has 122 (11.7%) zeros Zeros

Reproduction

Analysis started2025-09-11 01:08:45.928574
Analysis finished2025-09-11 01:08:52.252590
Duration6.32 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Ni
Real number (ℝ)

High correlation 

Distinct964
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.853901
Minimum42.430889
Maximum69.193821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:52.288393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum42.430889
5-th percentile53.682
Q158.489172
median59.732879
Q360.317993
95-th percentile61.654211
Maximum69.193821
Range26.762931
Interquartile range (IQR)1.8288211

Descriptive statistics

Standard deviation3.3408297
Coefficient of variation (CV)0.056764797
Kurtosis6.0539617
Mean58.853901
Median Absolute Deviation (MAD)0.70396861
Skewness-1.6444558
Sum61384.619
Variance11.161143
MonotonicityNot monotonic
2025-09-11T09:08:52.343650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.54 4
 
0.4%
60.25 3
 
0.3%
53.7 3
 
0.3%
61.05 3
 
0.3%
54.09 3
 
0.3%
54.27 3
 
0.3%
60.75 3
 
0.3%
60.64 3
 
0.3%
54.6 2
 
0.2%
59.33 2
 
0.2%
Other values (954) 1014
97.2%
ValueCountFrequency (%)
42.43088922 1
0.1%
42.62287882 1
0.1%
43.13088939 1
0.1%
43.23716989 1
0.1%
44.01258122 1
0.1%
44.18463914 1
0.1%
44.30656541 1
0.1%
44.49029806 1
0.1%
44.63518472 1
0.1%
44.64141439 1
0.1%
ValueCountFrequency (%)
69.19382059 1
0.1%
69.06917702 1
0.1%
69.0590177 1
0.1%
69.04477762 1
0.1%
68.97506747 1
0.1%
68.46856433 1
0.1%
68.33292657 1
0.1%
68.22024417 1
0.1%
67.99402312 1
0.1%
67.90362251 1
0.1%

Co
Real number (ℝ)

High correlation 

Distinct869
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.578523
Minimum0.78282388
Maximum27.881798
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:52.398369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.78282388
5-th percentile9.977593
Q110.091716
median10.284924
Q315.17
95-th percentile20.49438
Maximum27.881798
Range27.098975
Interquartile range (IQR)5.0782843

Descriptive statistics

Standard deviation4.011008
Coefficient of variation (CV)0.31887751
Kurtosis1.5437862
Mean12.578523
Median Absolute Deviation (MAD)0.86678061
Skewness0.76067078
Sum13119.399
Variance16.088185
MonotonicityNot monotonic
2025-09-11T09:08:52.454369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.17 12
 
1.2%
15.16 12
 
1.2%
15.18 11
 
1.1%
15.14 11
 
1.1%
15.15 11
 
1.1%
15.13 10
 
1.0%
15.2 9
 
0.9%
15.23 9
 
0.9%
15.19 9
 
0.9%
15.12 8
 
0.8%
Other values (859) 941
90.2%
ValueCountFrequency (%)
0.782823884 1
0.1%
0.841761139 1
0.1%
0.842413581 1
0.1%
0.861704919 1
0.1%
1.079741348 1
0.1%
1.3665661 1
0.1%
1.530981468 1
0.1%
1.711031277 1
0.1%
1.915495303 1
0.1%
2.095247084 1
0.1%
ValueCountFrequency (%)
27.88179844 1
0.1%
27.68347206 1
0.1%
27.20138191 1
0.1%
27.00048618 1
0.1%
26.46513744 1
0.1%
26.15427705 1
0.1%
26.13898091 1
0.1%
25.90568056 1
0.1%
25.71833306 1
0.1%
25.67223522 1
0.1%

Al
Real number (ℝ)

High correlation 

Distinct723
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1149872
Minimum0.43
Maximum6.0140314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:52.512387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.43
5-th percentile1.093
Q12.29
median4.9280088
Q35.091859
95-th percentile5.4959624
Maximum6.0140314
Range5.5840314
Interquartile range (IQR)2.801859

Descriptive statistics

Standard deviation1.4859564
Coefficient of variation (CV)0.36110839
Kurtosis-0.64030329
Mean4.1149872
Median Absolute Deviation (MAD)0.30394331
Skewness-0.96475989
Sum4291.9317
Variance2.2080664
MonotonicityNot monotonic
2025-09-11T09:08:52.561386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 122
 
11.7%
2.16 14
 
1.3%
2.19 14
 
1.3%
2.26 11
 
1.1%
2.25 11
 
1.1%
2.23 11
 
1.1%
2.2 11
 
1.1%
2.27 11
 
1.1%
2.22 11
 
1.1%
2.21 10
 
1.0%
Other values (713) 817
78.3%
ValueCountFrequency (%)
0.43 1
 
0.1%
0.47 1
 
0.1%
0.48 2
0.2%
0.51 2
0.2%
0.52 2
0.2%
0.53 2
0.2%
0.54 1
 
0.1%
0.56 1
 
0.1%
0.58 1
 
0.1%
0.61 3
0.3%
ValueCountFrequency (%)
6.014031387 1
0.1%
5.944539913 1
0.1%
5.881887 1
0.1%
5.855789928 1
0.1%
5.824797846 1
0.1%
5.823299012 1
0.1%
5.817082677 1
0.1%
5.785378297 1
0.1%
5.77011 1
0.1%
5.754069082 1
0.1%

Ti
Real number (ℝ)

High correlation  Zeros 

Distinct622
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.012801
Minimum0
Maximum6.7886261
Zeros121
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:52.612476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.3001213
median2.4366609
Q34.57
95-th percentile5.1901958
Maximum6.7886261
Range6.7886261
Interquartile range (IQR)2.2698787

Descriptive statistics

Standard deviation1.6638329
Coefficient of variation (CV)0.55225451
Kurtosis-0.76022285
Mean3.012801
Median Absolute Deviation (MAD)2.0445519
Skewness-0.23464646
Sum3142.3514
Variance2.76834
MonotonicityNot monotonic
2025-09-11T09:08:52.666476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 121
 
11.6%
4.56 43
 
4.1%
4.57 35
 
3.4%
4.59 30
 
2.9%
4.58 27
 
2.6%
4.53 26
 
2.5%
4.61 25
 
2.4%
4.6 23
 
2.2%
4.55 20
 
1.9%
4.54 18
 
1.7%
Other values (612) 675
64.7%
ValueCountFrequency (%)
0 121
11.6%
0.312987183 1
 
0.1%
0.359741809 1
 
0.1%
0.400097851 1
 
0.1%
0.446025788 1
 
0.1%
0.458145096 1
 
0.1%
0.477838113 1
 
0.1%
0.478229502 1
 
0.1%
0.47840803 1
 
0.1%
0.520561249 1
 
0.1%
ValueCountFrequency (%)
6.78862611 1
0.1%
6.757747624 1
0.1%
6.754479187 1
0.1%
6.74243541 1
0.1%
6.654160157 1
0.1%
6.605689791 1
0.1%
6.561613963 1
0.1%
6.543287372 1
0.1%
6.428789095 1
0.1%
6.395960533 1
0.1%

W
Real number (ℝ)

High correlation 

Distinct867
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4516112
Minimum0.38
Maximum10.560094
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:52.721487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.38
5-th percentile1.17
Q11.8165917
median7.1884118
Q37.5349643
95-th percentile7.817414
Maximum10.560094
Range10.180094
Interquartile range (IQR)5.7183726

Descriptive statistics

Standard deviation2.7810847
Coefficient of variation (CV)0.51013995
Kurtosis-1.3232682
Mean5.4516112
Median Absolute Deviation (MAD)0.50985663
Skewness-0.62806732
Sum5686.0305
Variance7.7344321
MonotonicityNot monotonic
2025-09-11T09:08:52.777487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.22 14
 
1.3%
1.2 12
 
1.2%
1.21 12
 
1.2%
1.19 12
 
1.2%
1.23 12
 
1.2%
1.17 10
 
1.0%
1.18 8
 
0.8%
1.16 8
 
0.8%
1.25 8
 
0.8%
1.15 8
 
0.8%
Other values (857) 939
90.0%
ValueCountFrequency (%)
0.38 1
0.1%
0.4 1
0.1%
0.41 1
0.1%
0.45 1
0.1%
0.46 1
0.1%
0.47 1
0.1%
0.48 1
0.1%
0.55 1
0.1%
0.56 1
0.1%
0.57 1
0.1%
ValueCountFrequency (%)
10.56009364 1
0.1%
10.50409759 1
0.1%
10.49819511 1
0.1%
10.44373928 1
0.1%
10.22420002 1
0.1%
10.17657702 1
0.1%
10.11241466 1
0.1%
9.962733495 1
0.1%
9.819802458 1
0.1%
9.770887316 1
0.1%

Ta
Real number (ℝ)

High correlation  Zeros 

Distinct608
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9291197
Minimum0
Maximum8.4781998
Zeros436
Zeros (%)41.8%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:52.954852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2.3799851
Q32.9107861
95-th percentile6.5017096
Maximum8.4781998
Range8.4781998
Interquartile range (IQR)2.9107861

Descriptive statistics

Standard deviation2.0782639
Coefficient of variation (CV)1.077312
Kurtosis0.60031729
Mean1.9291197
Median Absolute Deviation (MAD)2.3799851
Skewness0.99690588
Sum2012.0719
Variance4.3191808
MonotonicityNot monotonic
2025-09-11T09:08:53.006058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 436
41.8%
2.737450645 1
 
0.1%
2.276688677 1
 
0.1%
2.263070855 1
 
0.1%
2.337358113 1
 
0.1%
2.415319016 1
 
0.1%
2.555569016 1
 
0.1%
2.656458532 1
 
0.1%
2.6577615 1
 
0.1%
2.857396065 1
 
0.1%
Other values (598) 598
57.3%
ValueCountFrequency (%)
0 436
41.8%
0.240493161 1
 
0.1%
0.24243779 1
 
0.1%
0.254634823 1
 
0.1%
0.272912758 1
 
0.1%
0.280206919 1
 
0.1%
0.323140742 1
 
0.1%
0.372096549 1
 
0.1%
0.385729016 1
 
0.1%
0.40336189 1
 
0.1%
ValueCountFrequency (%)
8.478199839 1
0.1%
8.410074532 1
0.1%
8.239277177 1
0.1%
8.207924516 1
0.1%
8.198776597 1
0.1%
8.129167355 1
0.1%
8.037796742 1
0.1%
8.021572984 1
0.1%
7.984546984 1
0.1%
7.967445532 1
0.1%

Cr
Real number (ℝ)

High correlation 

Distinct764
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.389756
Minimum8.502037
Maximum14.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:53.055556image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum8.502037
5-th percentile8.6347169
Q18.8152662
median8.8809666
Q313.94
95-th percentile14.11
Maximum14.2
Range5.697963
Interquartile range (IQR)5.1247338

Descriptive statistics

Standard deviation2.3948188
Coefficient of variation (CV)0.23049808
Kurtosis-1.2450249
Mean10.389756
Median Absolute Deviation (MAD)0.093647459
Skewness0.86583246
Sum10836.515
Variance5.7351571
MonotonicityNot monotonic
2025-09-11T09:08:53.109671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.07 25
 
2.4%
14.08 24
 
2.3%
14.1 18
 
1.7%
14.09 18
 
1.7%
14.06 16
 
1.5%
13.95 15
 
1.4%
13.99 11
 
1.1%
13.91 11
 
1.1%
13.94 10
 
1.0%
13.93 10
 
1.0%
Other values (754) 885
84.9%
ValueCountFrequency (%)
8.502037032 1
0.1%
8.507768129 1
0.1%
8.532856129 1
0.1%
8.533136903 1
0.1%
8.534433419 1
0.1%
8.540040645 1
0.1%
8.547861032 1
0.1%
8.549933806 1
0.1%
8.551354194 1
0.1%
8.553080129 1
0.1%
ValueCountFrequency (%)
14.2 1
 
0.1%
14.19 2
 
0.2%
14.18 2
 
0.2%
14.17 4
0.4%
14.16 9
0.9%
14.15 8
0.8%
14.14 6
0.6%
14.13 9
0.9%
14.12 9
0.9%
14.11 9
0.9%

Mo
Real number (ℝ)

High correlation 

Distinct821
Distinct (%)78.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4837672
Minimum0.63
Maximum4.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:53.165180image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.63
5-th percentile0.86325785
Q10.91081582
median1.0160876
Q32.425
95-th percentile2.84
Maximum4.09
Range3.46
Interquartile range (IQR)1.5141842

Descriptive statistics

Standard deviation0.84562385
Coefficient of variation (CV)0.5699168
Kurtosis-0.078400632
Mean1.4837672
Median Absolute Deviation (MAD)0.13038482
Skewness1.1919348
Sum1547.5692
Variance0.7150797
MonotonicityNot monotonic
2025-09-11T09:08:53.218785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.75 28
 
2.7%
2.76 24
 
2.3%
2.78 22
 
2.1%
2.79 22
 
2.1%
2.74 20
 
1.9%
2.73 18
 
1.7%
2.77 17
 
1.6%
2.8 14
 
1.3%
2.84 10
 
1.0%
2.85 9
 
0.9%
Other values (811) 859
82.4%
ValueCountFrequency (%)
0.63 1
0.1%
0.65 1
0.1%
0.66 2
0.2%
0.7 1
0.1%
0.75 1
0.1%
0.78 1
0.1%
0.8 1
0.1%
0.821701435 1
0.1%
0.828027848 1
0.1%
0.828317671 1
0.1%
ValueCountFrequency (%)
4.09 1
0.1%
4.08 1
0.1%
4.06 1
0.1%
4.05 2
0.2%
4.03 2
0.2%
4.01 1
0.1%
3.99 1
0.1%
3.95 2
0.2%
3.87 1
0.1%
3.85 1
0.1%

Nb
Real number (ℝ)

High correlation  Zeros 

Distinct617
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1082598
Minimum0
Maximum8.0417135
Zeros122
Zeros (%)11.7%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:53.274292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.98
median2.3676159
Q32.5992291
95-th percentile6.272684
Maximum8.0417135
Range8.0417135
Interquartile range (IQR)1.6192291

Descriptive statistics

Standard deviation1.7347901
Coefficient of variation (CV)0.82285403
Kurtosis1.8284035
Mean2.1082598
Median Absolute Deviation (MAD)1.3676159
Skewness1.3503321
Sum2198.915
Variance3.0094967
MonotonicityNot monotonic
2025-09-11T09:08:53.330867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 122
 
11.7%
0.98 93
 
8.9%
0.99 70
 
6.7%
0.97 58
 
5.6%
1 37
 
3.5%
0.96 21
 
2.0%
1.01 21
 
2.0%
1.02 11
 
1.1%
2.612086305 2
 
0.2%
5.373672302 1
 
0.1%
Other values (607) 607
58.2%
ValueCountFrequency (%)
0 122
11.7%
0.234188093 1
 
0.1%
0.23874534 1
 
0.1%
0.240135901 1
 
0.1%
0.248169551 1
 
0.1%
0.2498003 1
 
0.1%
0.266189957 1
 
0.1%
0.289096289 1
 
0.1%
0.351203799 1
 
0.1%
0.430200304 1
 
0.1%
ValueCountFrequency (%)
8.041713508 1
0.1%
8.029784248 1
0.1%
7.971233068 1
0.1%
7.951161482 1
0.1%
7.945535419 1
0.1%
7.935002226 1
0.1%
7.838456311 1
0.1%
7.833657856 1
0.1%
7.672316082 1
0.1%
7.597639084 1
0.1%

Zr
Real number (ℝ)

High correlation 

Distinct714
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.034867648
Minimum0.02
Maximum0.048665742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:53.383334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.028645657
Q10.03
median0.0350464
Q30.039181262
95-th percentile0.042202597
Maximum0.048665742
Range0.028665742
Interquartile range (IQR)0.009181262

Descriptive statistics

Standard deviation0.0047163658
Coefficient of variation (CV)0.13526481
Kurtosis-0.97771969
Mean0.034867648
Median Absolute Deviation (MAD)0.0049536
Skewness0.080361902
Sum36.366957
Variance2.2244106 × 10-5
MonotonicityNot monotonic
2025-09-11T09:08:53.436337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.03 241
 
23.1%
0.04 70
 
6.7%
0.02 3
 
0.3%
0.0360047 2
 
0.2%
0.040552451 2
 
0.2%
0.03660971 2
 
0.2%
0.037382532 2
 
0.2%
0.027146268 2
 
0.2%
0.036519179 2
 
0.2%
0.035594 2
 
0.2%
Other values (704) 715
68.6%
ValueCountFrequency (%)
0.02 3
0.3%
0.024189347 1
 
0.1%
0.02488074 1
 
0.1%
0.025891765 1
 
0.1%
0.026099484 1
 
0.1%
0.026338224 1
 
0.1%
0.026441573 1
 
0.1%
0.026767289 1
 
0.1%
0.026840748 1
 
0.1%
0.026909198 1
 
0.1%
ValueCountFrequency (%)
0.048665742 1
0.1%
0.046921371 1
0.1%
0.046784471 1
0.1%
0.045168168 1
0.1%
0.044929697 1
0.1%
0.044636024 1
0.1%
0.044598487 1
0.1%
0.04449083 1
0.1%
0.044335727 1
0.1%
0.044196297 1
0.1%

B
Categorical

High correlation 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size54.1 KiB
0.01
729 
0.02
314 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4172
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.02
2nd row0.02
3rd row0.02
4th row0.02
5th row0.02

Common Values

ValueCountFrequency (%)
0.01 729
69.9%
0.02 314
30.1%

Length

2025-09-11T09:08:53.483868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-09-11T09:08:53.511893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0.01 729
69.9%
0.02 314
30.1%

Most occurring characters

ValueCountFrequency (%)
0 2086
50.0%
. 1043
25.0%
1 729
 
17.5%
2 314
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3129
75.0%
Other Punctuation 1043
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2086
66.7%
1 729
 
23.3%
2 314
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 1043
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4172
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2086
50.0%
. 1043
25.0%
1 729
 
17.5%
2 314
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2086
50.0%
. 1043
25.0%
1 729
 
17.5%
2 314
 
7.5%

C
Real number (ℝ)

High correlation 

Distinct123
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.029395973
Minimum0.002479339
Maximum0.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:53.550427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.002479339
5-th percentile0.01
Q10.01
median0.01
Q30.02
95-th percentile0.17082645
Maximum0.3
Range0.29752066
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.053300325
Coefficient of variation (CV)1.8131846
Kurtosis11.323117
Mean0.029395973
Median Absolute Deviation (MAD)0
Skewness3.4663208
Sum30.66
Variance0.0028409246
MonotonicityNot monotonic
2025-09-11T09:08:53.604435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 608
58.3%
0.02 314
30.1%
0.297520661 1
 
0.1%
0.295041322 1
 
0.1%
0.218181818 1
 
0.1%
0.215702479 1
 
0.1%
0.21322314 1
 
0.1%
0.210743802 1
 
0.1%
0.208264463 1
 
0.1%
0.205785124 1
 
0.1%
Other values (113) 113
 
10.8%
ValueCountFrequency (%)
0.002479339 1
 
0.1%
0.004958678 1
 
0.1%
0.007438017 1
 
0.1%
0.009917355 1
 
0.1%
0.01 608
58.3%
0.012396694 1
 
0.1%
0.014876033 1
 
0.1%
0.017355372 1
 
0.1%
0.019834711 1
 
0.1%
0.02 314
30.1%
ValueCountFrequency (%)
0.3 1
0.1%
0.297520661 1
0.1%
0.295041322 1
0.1%
0.292561983 1
0.1%
0.290082645 1
0.1%
0.287603306 1
0.1%
0.285123967 1
0.1%
0.282644628 1
0.1%
0.280165289 1
0.1%
0.27768595 1
0.1%

Target
Real number (ℝ)

High correlation 

Distinct1042
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83591633
Minimum0.000406478
Maximum2.4545219
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2025-09-11T09:08:53.659441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.000406478
5-th percentile0.03188817
Q10.22505989
median0.87442145
Q31.3187896
95-th percentile1.7795184
Maximum2.4545219
Range2.4541155
Interquartile range (IQR)1.0937297

Descriptive statistics

Standard deviation0.60894973
Coefficient of variation (CV)0.72848167
Kurtosis-1.1881443
Mean0.83591633
Median Absolute Deviation (MAD)0.57332992
Skewness0.17665224
Sum871.86074
Variance0.37081977
MonotonicityNot monotonic
2025-09-11T09:08:53.712495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.280306972 2
 
0.2%
0.171384517 1
 
0.1%
0.462198936 1
 
0.1%
0.628339891 1
 
0.1%
0.757213623 1
 
0.1%
0.651956241 1
 
0.1%
0.526815329 1
 
0.1%
0.536347229 1
 
0.1%
0.596228159 1
 
0.1%
0.425676921 1
 
0.1%
Other values (1032) 1032
98.9%
ValueCountFrequency (%)
0.000406478 1
0.1%
0.000528421 1
0.1%
0.000535196 1
0.1%
0.000812955 1
0.1%
0.001219433 1
0.1%
0.001293954 1
0.1%
0.001768178 1
0.1%
0.003360215 1
0.1%
0.003468609 1
0.1%
0.00390896 1
0.1%
ValueCountFrequency (%)
2.454521928 1
0.1%
2.435512324 1
0.1%
2.35364773 1
0.1%
2.353207379 1
0.1%
2.224001691 1
0.1%
2.15852492 1
0.1%
2.140497637 1
0.1%
2.130240852 1
0.1%
2.12644706 1
0.1%
2.109957618 1
0.1%

Interactions

2025-09-11T09:08:51.670495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-09-11T09:08:49.082655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-09-11T09:08:47.498317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:47.984808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:48.446377image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:49.005274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:49.472874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:49.980599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:50.481948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:51.096696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:51.591487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:52.110263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:46.620582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:47.078970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:47.540930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:48.026315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:48.487165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:49.045013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:49.515570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:50.022791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:50.525158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:51.142013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-09-11T09:08:51.631496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-09-11T09:08:53.756548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AlBCCoCrMoNbNiTaTargetTiWZr
Al1.0000.997-0.659-0.479-0.735-0.5720.3860.0850.5670.513-0.4170.5710.331
B0.9971.0000.2030.9260.9980.9270.9400.5130.7290.7520.9440.9040.702
C-0.6590.2031.0000.3300.5800.656-0.321-0.212-0.262-0.2400.264-0.567-0.134
Co-0.4790.9260.3301.0000.4450.603-0.228-0.495-0.701-0.5270.665-0.431-0.291
Cr-0.7350.9980.5800.4451.0000.540-0.3240.021-0.691-0.5000.538-0.598-0.437
Mo-0.5720.9270.6560.6030.5401.000-0.459-0.249-0.500-0.3030.605-0.602-0.148
Nb0.3860.940-0.321-0.228-0.324-0.4591.000-0.0360.1120.086-0.5720.476-0.206
Ni0.0850.513-0.212-0.4950.021-0.249-0.0361.0000.1510.450-0.0290.091-0.018
Ta0.5670.729-0.262-0.701-0.691-0.5000.1120.1511.0000.686-0.6810.2300.605
Target0.5130.752-0.240-0.527-0.500-0.3030.0860.4500.6861.000-0.3390.2700.470
Ti-0.4170.9440.2640.6650.5380.605-0.572-0.029-0.681-0.3391.000-0.347-0.153
W0.5710.904-0.567-0.431-0.598-0.6020.4760.0910.2300.270-0.3471.0000.183
Zr0.3310.702-0.134-0.291-0.437-0.148-0.206-0.0180.6050.470-0.1530.1831.000

Missing values

2025-09-11T09:08:52.172249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-09-11T09:08:52.221447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

NiCoAlTiWTaCrMoNbZrBCTarget
053.5321.402.234.610.380.014.072.740.970.030.020.020.171385
153.6721.252.164.620.400.014.132.720.980.030.020.020.114124
253.5121.342.224.590.410.014.152.740.970.030.020.020.118864
353.5921.262.244.590.450.014.102.730.970.030.020.020.075920
453.5221.252.274.600.460.014.142.730.960.030.020.020.120216
553.6221.202.204.630.470.014.102.750.960.030.020.020.149167
653.6821.072.234.610.480.014.122.750.990.030.020.020.123625
753.7021.102.114.630.570.014.122.720.980.030.020.020.084258
853.8321.052.094.560.550.014.122.750.980.030.020.020.185537
953.7521.052.224.590.560.014.062.730.970.030.020.020.112066
NiCoAlTiWTaCrMoNbZrBCTarget
103359.59978910.1363855.1915132.3219447.1830672.8370828.9387230.9420612.5222450.0395040.010.2776861.654588
103459.72298910.1630624.7419222.3458837.3871532.9037788.9423240.9161842.5486200.0379210.010.2801651.619529
103560.03355110.0976974.7992802.3490707.2208082.8341248.9115300.9253922.5004680.0354350.010.2826451.498554
103659.87741210.1245764.8846772.3432227.1884122.8481218.9209030.9650642.5151060.0373830.010.2851241.665718
103759.78152310.1347494.7373882.3541207.3117642.9088278.9302510.9601122.5458780.0377840.010.2876031.281502
103859.85720610.1389784.8127282.3430777.1942422.8982778.9274930.9384752.5493130.0401290.010.2900831.558754
103959.83478510.1140974.8503362.3523407.1651332.9500528.9275670.9306422.5348850.0376030.010.2925621.567364
104060.03472110.0686434.6503262.3399897.2368202.9268888.9350650.9336142.5358130.0330790.010.2950411.868144
104159.84880410.1471944.8606582.3392997.2476432.8424128.9369310.9395182.4916900.0383300.010.2975211.380967
104259.80407810.0878464.9104892.3448027.2127872.8918438.9281040.9310972.5406530.0383010.010.3000001.464329